fbrc/MBartTranslator

mBART-50

mBART-50 is a multilingual Sequence-to-Sequence model pre-trained using the "Multilingual Denoising Pretraining" objective. It was introduced in Multilingual Translation with Extensible Multilingual Pretraining and Finetuning paper.

Model description

mBART-50 is a multilingual Sequence-to-Sequence model. It was introduced to show that multilingual translation models can be created through multilingual fine-tuning. Instead of fine-tuning on one direction, a pre-trained model is fine-tuned on many directions simultaneously. mBART-50 is created using the original mBART model and extended to add extra 25 languages to support multilingual machine translation models of 50 languages. The pre-training objective is explained below.

Docker with GPU

docker run -it --gpus all -p 7860:7860 --platform=linux/amd64 \
	registry.hf.space/wall-e-zz-mbarttranslator:latest python app.py

Docker with CPU

docker run -it -p 7860:7860 --platform=linux/amd64 \
	registry.hf.space/wall-e-zz-mbarttranslator:latest python app.py